基于MGWR模型的中国大陆结核病的影响因素
1State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China.
PloS one
|August 31, 2023
概括
中国的结核病发病率显示出空间集群和异质性. 多尺度地理加权回归 (MGWR) 模型准确预测结核病分布,为公共卫生干预提供可靠的数据.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 空间分析 空间分析
背景情况:
- 结核病 (TB) 仍然是一个全球性的健康问题,特别是在高发病率地区,如中国大陆.
- 由于COVID-19大流行扰乱了医疗资源,人们对最近的结核病数据的可靠性感到担忧.
- 本研究侧重于2014-2018年结核病发病率数据,以确保数据的真实性.
研究的目的:
- 分析中国大陆结核病发病率的时间和空间分布.
- 研究11个关键因素对结核病发病率的影响.
- 为结核病数据分析和公共卫生决策制定可靠的模型.
主要方法:
- 空间自相关性分析以确定结核病患者分布模式.
- 多尺度地理加权回归 (MGWR) 模型应用.
- 与普通最小平方 (OLS) 和地理加权回归 (GWR) 模型进行比较.
主要成果:
- 中国大陆的结核病患者分布表现出显著的空间聚合和异质性.
- MGWR模型实现了优异的性能,R2为0.932和调整后的R2为0.910.
- MGWR模型的准确度指标 (MAE,MSE,MAPE) 显著优于OLS和GWR模型.
结论:
- MGWR模型提供了一种可靠和准确的方法来分析结核病发病率数据.
- 这些发现为中国和全球结核病预防和控制提供了宝贵的决策参考.
- 利用大流行前的数据确保了对结核病流行病学的洞察力的可靠性.
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